3 citations · 6 across the 6 of their papers we have counts for
9 papers
Directional density-based clustering
Paula Saavedra-Nieves, Martín Fernández-Pérez
Density-based clustering methodology has been widely considered in the statistical literature for classifying Euclidean observations. However, this approach has not been contemplat…
Nonparametric estimation of highest density regions for COVID-19
Paula Saavedra-Nieves
Highest density regions refer to level sets containing points of relatively high density. Their estimation from a random sample, generated from the underlying density, allows to de…
On systems of quotas based on bankruptcy with a priori unions: estimating random arrival-style rules
A. Saavedra-Nieves, P. Saavedra-Nieves
This paper addresses a sampling procedure for estimating extensions of the random arrival rule to those bankruptcy situations where there exist a priori unions. It is based on simp…
Nonparametric estimation of directional highest density regions
Paula Saavedra-Nieves, Rosa María Crujeiras
Reconstruction of sets from a random sample of points intimately related to them is the goal of set estimation theory. Within this context, a particular problem is the one related…
Extent of occurrence reconstruction using a new data-driven support estimator
A. Rodríguez-Casal, P. Saavedra-Nieves
Given a random sample of points from some unknown distribution, we propose a new data-driven method for estimating its probability support S. Under the mild assumption that S is r-…
Minimax Hausdorff estimation of density level sets
Alberto Rodríguez-Casal, Paula Saavedra-Nieves
Given a random sample of points from some unknown density, we propose a data-driven method for estimating density level sets under the r-convexity assumption. This shape condition…
A fully data-driven method for estimating density level sets
A. Rodríguez-Casal, P. Saavedra-Nieves
Density level sets can be estimated using plug-in methods, excess mass algorithms or a hybrid of the two previous methodologies. The plug-in algorithms are based on replacing the u…
A fully data-driven method for estimating the shape of a point cloud
Alberto Rodríguez-Casal, Paula Saavedra-Nieves
Given a random sample of points from some unknown distribution, we propose a new data-driven method for estimating its probability support . Under the mild assumption that i…
A comparative simulation study of data-driven methods for estimating density level sets
Paula Saavedra-Nieves, Wenceslao González-Manteiga, Alberto Rodríguez-Casal
Density level sets are mainly estimated using one of three methodologies: plug-in, excess mass, or a hybrid approach. The plug-in methods are based on replacing the unknown density…